There are known adaptation devices that adapt an estimation model, which is a regression model created through machine learning using learning data for a general environment, to a specific environment. For example, when a general estimation model for estimating the number of persons contained in an image is adapted to an estimation system that estimates the number of pedestrians on the basis of a captured image of a passage of a station or other locations, such an adaptation device uses images captured by an image-capturing device installed in the passage of the station or other locations to modify the general estimation model. An adaptation technique of this type is called domain adaptation, transfer learning, or knowledge transfer, for example.
When adapting a general estimation model to a specific environment, the adaptation device modifies parameters included in the estimation model. However, the estimation model includes many parameters. Thus, the adaptation device needs to adjust these parameters appropriately at great expense of time and computation cost.